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The current trend toward machine-scoring of student work, Ericsson and Haswell argue, has created an emerging issue with implications for higher education across the disciplines, but with particular importance for those in English departments and in administration. The academic community has been silent on the issue—some would say excluded from it—while the commercial entities who develop essay-scoring software have been very active.

Machine Scoring of Student Essays is the first volume to seriously consider the educational mechanisms and consequences of this trend, and it offers important discussions from some of the leading scholars in writing assessment.

Reading and evaluating student writing is a time-consuming process, yet it is a vital part of both student placement and coursework at post-secondary institutions. In recent years, commercial computer-evaluation programs have been developed to score student essays in both of these contexts. Two-year colleges have been especially drawn to these programs, but four-year institutions are moving to them as well, because of the cost-savings they promise. Unfortunately, to a large extent, the programs have been written, and institutions are installing them, without attention to their instructional validity or adequacy.

Since the education software companies are moving so rapidly into what they perceive as a promising new market, a wider discussion of machine-scoring is vital if scholars hope to influence development and/or implementation of the programs being created. What is needed, then, is a critical resource to help teachers and administrators evaluate programs they might be considering, and to more fully envision the instructional consequences of adopting them. And this is the resource that Ericsson and Haswell are providing here.

College and university faculty in the arts (visual, studio, language, music, design, and others) regularly grade and assess undergraduate student work but often with little guidance or support. As a result, many arts faculty, especially new faculty, adjunct faculty, and graduate student instructors, feel bewildered and must “reinvent the wheel” when grappling with the challenges and responsibilities of grading and assessing student work.

Meaningful Grading: A Guide for Faculty in the Arts enables faculty to create and implement effective assessment methodologies—research based and field tested—in traditional and online classrooms. In doing so, the book reveals how the daunting challenges of grading in the arts can be turned into opportunities for deeper student learning, increased student engagement, and an enlivened pedagogy.

In the face of the continuing discourse of crisis in US education, The Meaningful Writing Project offers readers an affirming story of writing in higher education that shares students’ experiences in their own voices. In presenting the results of a three-year study consisting of surveys and interviews of university seniors and their faculty across three diverse institutions, authors Michele Eodice, Anne Ellen Geller, and Neal Lerner consider students’ perceptions of their meaningful writing experiences, the qualities of those experiences, and instructors’ perspectives on assignment design and delivery.

This study confirms that meaningful assignments offer students opportunities to engage with instructors, peers, and texts and are relevant to past experiences and passions as well as to future aspirations and identities. Meaningful writing occurs across majors, in both required and elective courses, and beyond students’ years at college. Additionally, the study makes clear that faculty across the curriculum devote significant care and attention to creating writing assignments that support student learning, as they understand writing performance to be a developmental process connected to overall cognitive and social development, student engagement with learning, and success in a wide variety of disciplines and professions.

The Meaningful Writing Project provides writing center directors, WPAs, other composition scholars, and all faculty interested in teaching and learning with writing an unprecedented look into the writing projects students find meaningful.

Start-ups and other entrepreneurial ventures make a significant contribution to the US economy, particularly in the tech sector, where they comprise some of the largest and most influential companies. Yet for every high-profile, high-growth company like Apple, Facebook, Microsoft, and Google, many more fail. This enormous heterogeneity poses conceptual and measurement challenges for economists concerned with understanding their precise impact on economic growth.
           
Measuring Entrepreneurial Businesses brings together economists and data analysts to discuss the most recent research covering three broad themes. The first chapters isolate high- and low-performing entrepreneurial ventures and analyze their roles in creating jobs and driving innovation and productivity. The next chapters turn the focus on specific challenges entrepreneurs face and how they have varied over time, including over business cycles. The final chapters explore core measurement issues, with a focus on new data projects under development that may improve our understanding of this dynamic part of the economy.
 

Measuring Functioning and Well-Being is a comprehensive account a broad range of self-reported functioning and well-being measures developed for the Medical Outcomes Study, a large-sale study of how patients fare with health care in the United States. This book provides a set of ready-to-use generic measures that are applicable to all adults, including those well and chronically ill, as well as a methodological guide to collecting health data and constructing health measures. As demand increases for more practical methods to monitor the outcomes of health care, this volume offers a timely and valuable contribution to the field.
The contributors address conceptual and methodological issues involved in measuring such important health status concepts as: physical, social, and role functioning; psychological distress and well-being; general health perceptions; energy and fatigue; sleep; and pain. The authors present psychometric results and explain how to administer, score, and interpret the measures.
Comprising the work of a number of highly respected scholars in the field of health assessment, Measuring Functioning and Well-Being will be of great interest and value to the growing number of researchers, policymakers, and clinicians concerned with the management and evaluation of health care.

Social science research often yields conflicting results: Does juvenile delinquent rehabilitation work? Is teenage pregnancy prevention effective? In an effort to improve the value of research for shaping social policy, social scientists are increasingly employing a powerful technique called meta-analysis. By systematically pulling together findings of a particular research problem, meta-analysis allows researchers to synthesize the results of multiple studies and detect statistically significant patterns among them. Meta-Analysis for Explanation brings exemplary illustrations of research synthesis together with expert discussion of the use of meta-analytic techniques. The emphasis throughout is on the explanatory applications of meta-analysis, a quality that makes this casebook distinct from other treatments of this methodology. The book features four detailed case studies by Betsy Jane Becker, Elizabeth C. Devine, Mark W. Lipsey, and William R. Shadish, Jr. These are offered as meta-analyses that seek both to answer the descriptive questions to which research synthesis is traditionally directed in the health and social sciences, and also to explore how a more systematic method of explanation might enhance the policy yield of research reviews. To accompany these cases, a group of the field's leading scholars has written several more general chapters that discuss the history of research synthesis, the use of meta-analysis and its value for scientific explanation, and the practical issues and challenges facing researchers who want to try this new technique. As a practical resource, Meta-Analysis for Explanation guides social scientists to greater levels of sophistication in their efforts to synthesize the results of social research. "This is an important book...[it is] another step in the continuing exploration of the wider implications and powers of meta-analytic methods." —Contemporary Psychology

This volume's contributors evaluate the accomplishments, limits, and consequences of using quantitative metrics in global health. Whether analyzing maternal mortality rates, the relationships between political goals and metrics data, or the links between health outcomes and a program's fiscal support, the contributors question the ability of metrics to solve global health problems. They capture a moment when global health scholars and practitioners must evaluate the potential effectiveness and pitfalls of different metrics—even as they remain elusive and problematic.
 

Contributors. Vincanne Adams, Susan Erikson, Molly Hales, Pierre Minn, Adeola Oni-Orisan, Carolyn Smith-Morris, Marlee Tichenor, Lily Walkover, Claire L. Wendland